Comparative QSAR- And fragments distribution analysis of drugs, druglikes, metabolic substances, and antimicrobial compounds

Journal of Chemical Information and Modeling

Volumn 46, Issue 5, 2006, Pages 2167-2182

  Karakoc, Emre ^a   Sahinalp, S Cenk ^a   Cherkasov, Artem ^b,c  

^a SIMON FRASER UNIVERSITY   (Canada)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^c UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

BACTERIA; CLASSIFIERS; METABOLISM; NEURAL NETWORKS; OPTIMIZATION; SUGARS;

ANTIMICROBIAL COMPOUNDS; FRAGMENTS DISTRIBUTION ANALYSIS; LINEAR DISCRIMINATIVE ANALYSIS; METABOLIC SUBSTANCES;

DRUG PRODUCTS;

ANTIINFECTIVE AGENT; DRUG;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMICAL STRUCTURE; CHEMISTRY; QUANTITATIVE STRUCTURE ACTIVITY RELATION; STATISTICAL MODEL;

ANTI-INFECTIVE AGENTS; LINEAR MODELS; MODELS, MOLECULAR; NEURAL NETWORKS (COMPUTER); PHARMACEUTICAL PREPARATIONS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 33750321101     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci0601517     Document Type: Article

References (24)

1. Cherkasov. A. 'Inductive' Descriptors. 10 Successful Years in QSAR. Curr. Comput.-Aided Drug Des. 2005, 1, 21-42.
2. Cherkasov, A.; Jankovic, B. Application of 'Inductive' QSAR Descriptors for Quantification of Antibacterial Activity of Cationic Polypeptides. Molecules 2004, 9, 1034-1052.
3. Cherkasov, A.; Shi, Z.; Fallahi, M.; Hammond, G. L. Successful in Silico Discovery of Novel Non-Steroidal Ligands for Human Sex Hormone Binding Globulin. J. Med. Chem. 2005, 48, 3203-3213.
4. Cherkasov, A. Can 'Bacterial-Metabolite-Likeness' Model Improve Odds of 'In silico' Antibiotic Discovery? J. Chem. Inf. Model. 2006, 46, 1214-1222.
5. ChemIDPlus database: http://chem.sis.nlm.nih.gov/chemidplus/. May 2006.
6. J. Antibiot. database: http://www.nih.go.jp/~jun/NADB/byname.html, May 2006.
7. Tomas-Vert, F.; Perez-Gimenez, F.; Salabert-Salvador, M. T.; Garcia-March, F. J.; Jaen-Oltra, J. Artificial Neural Networks Applied to the Discrimination of Antibacterial Activity by Topological Methods. J. Mol. Struct. (THEOCHEM) 2000, 504, 249-259.
8. Cronin, M. T. D.; Aptula, A. O.; Dearden, J. C.; Duffy, J. C.; Netzeva, T. I.; Patel, H.; Rowe, P. H.; Schultz, T. W.; Worth, A. P.; Voutzoulidis, K.; Schuurmann, G. Structure-based classification of antibacterial activity. J. Chem. Inf. Comput. Sci. 2002, 42, 869-878.
9. Murcia-Soler, M.; Perez-Gimenez, F.; Garcia-March, F. J.; Salabert-Salvador, M. T.; Diaz-Villanueva, W.; Castro-Bleda, M. J.; Villanueva-Pareja, A. Artificial neural networks and linear discriminant analysis: a valuable combination in the selection of new antibacterial compounds. J. Chem. Inf. Comput. Sci. 2004, 44, 1031-1041.
10. The Merck Index 13.4 CD-ROM Edition; CambridgeSoft, Cambridge, MA, 2004.
11. Human Metabolite Database: http://redpoll.pharmacy.ualberta.ca/~aguo/ www_hmdb_ca/HMDB/, May 2006.
12. Analyticon Discovery Company: www.ac-discovery.com May 2006.
13. Assinex Gold Collection; Assinex Ltd.: Moscow, 2004.
14. Halgren, T. A. Merck molecular force field. 1. Basis, form, scope, parameterization, and performance of MMFF94. J. Comput. Chem. 1996, 17, 490-519.
15. Molecular Operational Environment; Chemical Computing Group Inc.: Montreal, Canada, 2005.
16. MOE SVL exchange community: http://svl.chemcomp.com/index.php, May 2006.
17. WEKA3: Data Mining Software in Java http://www.cs.waikato.ac.nz/~ml/weka/ . May 2006.
18. Zupan, J.; Gasteiger, J. Neural Networks in Chemistry and Drug Design, 2nd ed.; Wiley: New York, 1999; 380p.
19. Karakoc, E.; Cherkasov, A.; Sahinalp, S. C. Distance Based Algorithms for Small Biomolecule Classification and Structural Similarity Search; ISMB '06 Intelligent Systems for Molecular Biology, 2006.
20. CPLEX: High-performance software for mathematical programming http://www.ilog.com/products/cplex/, May 2006.
21. Xu, J.; Stevenson, J. Drug-like Index: A New Approach To Measure Drug-like Compounds and Their Diversity. J. Chem. Inf. Comput. Sci. 2006, 40, 1177-1187.
22. Irwin, J. J.; Shoichet, B. K. ZINC - a free database of commercially available compounds for virtual screening. J. Chem. Inf. Model. 2005, 45, 177-182.
23. Barabasi, A.-L. Linked: The New Science of Networks; Perseus Publ.: Cambridge, MA, 2002; 256p.
24. Livingston, D. J. Data analysis for chemists. Applications to QSAR and chemical product design; Oxford University Press: 1995; 324p.